PENDETEKSIAN KECURANGAN (FRAUD) LAPORAN KEUANGAN: ANALISIS KUANTITATIF BERBASIS SYSTEMATIC LITERATURE REVIEW 2020–2024

Aini Indrijawati, Mediaty Mediaty, Nursyafika Fitri, Muh. Nurtasriq Rusnawan, Dana Irfana

Abstract


Kecurangan laporan keuangan merupakan ancaman serius terhadap integritas pelaporan dan kepercayaan publik. Penelitian ini bertujuan untuk memetakan perkembangan, variabel, metode, dan temuan utama dalam penelitian kuantitatif tentang pendeteksian kecurangan laporan keuangan periode 2020–2024. Metode yang digunakan adalah Systematic Literature Review (SLR) dengan pedoman PRISMA, menganalisis 9 artikel empiris open access dari database ScienceDirect, MDPI, Emerald Insight, dan Garuda. Hasil sintesis menunjukkan tren penelitian bergeser dari fokus pada tata kelola perusahaan dan peran auditor menuju pemanfaatan teknologi analitik seperti machine learning yang mencapai akurasi deteksi 95–98%. Variabel paling konsisten yang memengaruhi fraud dan efektivitas deteksinya meliputi: kekuatan tata kelola perusahaan, tekanan keuangan, faktor psikologis, serta kompetensi dan teknologi auditor. Simpulan penelitian mengarah pada perlunya pendekatan integratif yang menggabungkan pengawasan struktural, pemahaman perilaku, dan teknologi prediktif untuk deteksi fraud yang efektif. Saran bagi penelitian mendatang adalah mengeksplorasi penerapan explainable AI dalam audit serta menguji interaksi faktor kelembagaan dan perilaku di berbagai setting regulasi.

Keywords


Kecurangan Laporan Keuangan; Pendeteksian Kecurangan; Systematic Literature Review; Tata Kelola Perusahaan; Machine Learning

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DOI: https://doi.org/10.32509/jakpi.v5i2.6305

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